Other packages > Find by keyword >

kcpRS  

Kernel Change Point Detection on the Running Statistics
View on CRAN: Click here


Download and install kcpRS package within the R console
Install from CRAN:
install.packages("kcpRS")

Install from Github:
library("remotes")
install_github("cran/kcpRS")

Install by package version:
library("remotes")
install_version("kcpRS", "1.1.1")



Attach the package and use:
library("kcpRS")
Maintained by
Kristof Meers
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2019-05-06
Latest Update: 2023-10-25
Description:
The running statistics of interest is first extracted using a time window which is slid across the time series, and in each window, the running statistics value is computed. KCP (Kernel Change Point) detection proposed by Arlot et al. (2012) is then implemented to flag the change points on the running statistics (Cabrieto et al., 2018, ). Change points are located by minimizing a variance criterion based on the pairwise similarities between running statistics which are computed via the Gaussian kernel. KCP can locate change points for a given k number of change points. To determine the optimal k, the KCP permutation test is first carried out by comparing the variance of the running statistics extracted from the original data to that of permuted data. If this test is significant, then there is sufficient evidence for at least one change point in the data. Model selection is then used to determine the optimal k>0.
How to cite:
Kristof Meers (2019). kcpRS: Kernel Change Point Detection on the Running Statistics. R package version 1.1.1, https://cran.r-project.org/web/packages/kcpRS
Previous versions and publish date:
1.0.0 (2019-05-06 11:00), 1.1.0 (2023-01-20 00:30)
Other packages that cited kcpRS R package
View kcpRS citation profile
Other R packages that kcpRS depends, imports, suggests or enhances
Downloads during the last 30 days
Get rewarded with contribution points by helping add
Reviews / comments / questions /suggestions ↴↴↴

Today's Hot Picks in Authors and Packages

mistral  
Methods in Structural Reliability
Various reliability analysis methods for rare event inference (computing failure probability and qua ...
Download / Learn more Package Citations See dependency  
critpath  
Setting the Critical Path in Project Management
Solving the problem of project management using CPM (Critical Path Method), PERT (Program Evaluation ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
rdbnomics  
Download DBnomics Data
R access to hundreds of millions data series from DBnomics API (). ...
Download / Learn more Package Citations See dependency  
steepness  
Testing Steepness of Dominance Hierarchies
The steepness package computes steepness as a property of dominance hierarchies. Steepness is define ...
Download / Learn more Package Citations See dependency  
ftaproxim  
Fault Tree Analysis Based on Proxel Simulation
Calculation and plotting of instantaneous unavailabilities of basic events along with the top event ...
Download / Learn more Package Citations See dependency  

22,114

R Packages

188,080

Dependencies

55,244

Author Associations

22,115

Publication Badges

© Copyright 2022 - present. All right reserved, rpkg.net. Contact Us / Suggestions / Concerns